Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add floomhq/moto --skill morninggit clone --depth 1 https://github.com/floomhq/motoWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/floomhq/moto/morning)<a href="https://agentmods.dev/skills/floomhq/moto/morning"><img src="https://agentmods.dev/badge/skills/floomhq/moto/morning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/floomhq/moto/morning"><img src="https://agentmods.dev/badge/skills/floomhq/moto/morning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00070 | $0.00685 |
| Opus 5 | $0.00035 | $0.00342 |
| Sonnet 5 | $0.00014 | $0.00137 |
| Haiku 4.5 | $0.00007 | $0.00068 |
Grade A, and why
morning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Morning Briefing Skill
Run a unified daily status check across all systems. Output a concise dashboard.
Steps
1. Unread Emails
Check unread count across accounts via IMAP. Do NOT read message bodies, only count.
import imaplib
accounts = [
# ("[email protected]", "app-password", "imap.gmail.com"),
]
for email, pw, server in accounts:
try:
m = imaplib.IMAP4_SSL(server)
m.login(email, pw)
m.select("INBOX", readonly=True) # readonly preserves unread status
_, data = m.search(None, "UNSEEN")
count = len(data[0].split()) if data[0] else 0
print(f"{email}: {count} unread")
m.logout()
except Exception as e:
print(f"{email}: ERROR {e}")
Use readonly=True (or BODY.PEEK[] for message reads) to preserve unread status.
2. Open GitHub Issues
# Switch to project account, list issues
# gh-<project>
gh issue list --state open --limit 20 2>/dev/null | head -20
3. Active Workplans
find ~ -name "WORKPLAN-*.md" -mtime -30 2>/dev/null | sort
4. Todos
cat ~/path/to/todos.md 2>/dev/null
5. System Health (Abbreviated)
# Docker containers
docker ps --format "table {{.Names}}\t{{.Status}}\t{{.Ports}}" 2>/dev/null
# Orphan check
pgrep -f "chrome-headless-shell|remotion|playwright" | wc -l
Output Format
Present as a concise dashboard table:
## Morning Briefing - YYYY-MM-DD
### Unread Email
| Account | Unread |
|-----------------------|--------|
| [email protected] | 3 |
| [email protected] | 0 |
### Open GitHub Issues
| Project | Count | Top Issue |
|------------|-------|-------------------------|
| my-project | 4 | #125 Critical bug (P0) |
### Active Workplans
- WORKPLAN-20260315-feature.md (12d ago)
### Todos
[contents of todo file]
### System Health
| Container | Status |
|------------|---------|
| my-app | Up 3d |
Orphan processes: 0
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 110 lines · 70 tokens per session scan A f2da41710bbc
morning is a skill published in the GitHub repository floomhq/moto (32 stars, last pushed 3mo ago), licensed MIT. It adds 70 tokens to every session and 685 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
rtk-optimizer
Wrap high-verbosity shell commands with RTK to reduce token consumption. Use when running git log, git diff, cargo test, pytest, or other verbose CLI output that wastes context window tokens.
session-save
Save the current session state (decisions, modified files, current status, and next steps) to a handoff file for later resume.
handoff-create
Generate a structured handoff document from the current session. Captures scope, relevant files with line numbers, key discoveries, work completed, current status, next steps, and code snippets. Use before ending a session or handing work to another agent.
handoff-update
Update an existing handoff document with current session progress. Applies section-specific merge rules: append-only for Work Done (never deletes history), replace for Status and Next Steps, merge for Files and Discoveries. Falls back to creating a new handoff if no source file is found.
handoff-resume
Load a handoff document and resume work from where a previous session left off. Parses scope, file references, completed work, and next steps, then confirms understanding before proceeding.
session
Session lifecycle management. Parent skill for session-related skills: learning (pattern extraction) and compact (context compression).